The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 03, 2026

Filed:

Oct. 29, 2021
Applicant:

Zhejiang University, Zhejiang, CN;

Inventors:

Jiming Chen, Zhejiang, CN;

Hang Zheng, Zhejiang, CN;

Chengwei Zhou, Zhejiang, CN;

Zhiguo Shi, Zhejiang, CN;

Assignee:

Zhejiang University, Zhejiang, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01S 3/14 (2006.01);
U.S. Cl.
CPC ...
G01S 3/143 (2013.01);
Abstract

Disclosed in the present invention is a method for estimating a direction of arrival of a sub-array partition type L-shaped coprime array based on fourth-order sampling covariance tensor denoising. The implementation steps are as follows: constructing an L-shaped coprime array partitioned with linear sub-arrays; modeling a receiving signal of the L-shaped coprime array and deriving a second-order cross-correlation matrix thereof; deriving a fourth-order covariance tensor based on the cross-correlation matrix; realizing fourth-order sampling covariance tensor denoising based on kernel tensor thresholding; deriving a fourth-order virtual domain signal based on denoised sampling covariance tensor; constructing a denoised structured virtual domain tensor; obtaining a direction of arrival estimation result by decomposing the structured virtual domain tensor. The present invention makes full use of the statistical distribution characteristics of the high-order tensor of the constructed sub-array partition type L-shaped coprime array, realizes high-precision two-dimensional direction of arrival estimation through denoised virtual domain tensor signal processing, and can be used for target positioning.


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